Published: Oct. 21, 2023
We describe our use of gridded glyphmaps to support development a repurposed COVID-19 infection model during the height pandemic. found that glyphmaps' ability interactive summarise multivariate input, intermediate results and outputs across multiple scales supported tasks in ways modellers had not previously seen. recount experiences, reflect on potential more spatial generally suggest areas further work.
Language: Английский
Computer Graphics Forum, Journal Year: 2025, Volume and Issue: unknown
Published: March 11, 2025
Abstract Static maps and animations remain popular in spatial epidemiology of dengue, limiting the analytical depth scope visualizations. Over half global population live dengue endemic regions. Understanding spatiotemporal dynamics four closely related serotypes, their immunological interactions, remains a challenge at scale. To facilitate this understanding, we worked with epidemiologists user‐centred design framework to create GeoDEN, an exploratory visualization tool that empowers experts investigate patterns serotype reports. The has several linked visualizations filtering mechanisms, enabling analysis range temporal scales. identify successes failures, present both insight‐based value‐driven evaluations. Our domain found GeoDEN valuable, verifying existing hypotheses uncovering novel insights warrant further investigation by community. developed visual exploration approach can be adapted for exploring other disease incident datasets.
Language: Английский
Citations
0
IEEE Computer Graphics and Applications, Journal Year: 2025, Volume and Issue: 45(1), P. 130 - 138
Published: Jan. 1, 2025
Data visualization methodologies were intensively leveraged during the COVID-19 pandemic. We review our design experience working on a set of interdisciplinary pandemic projects. describe challenges we met in these projects, characterize respective user communities, goals and tasks supported, data types visual media worked with. Furthermore, instantiate characterizations series case studies. Finally, analysis lessons learned, considering future pandemics.
Language: Английский
Citations
0
Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, Journal Year: 2022, Volume and Issue: 380(2233)
Published: Aug. 15, 2022
We report on an ongoing collaboration between epidemiological modellers and visualization researchers by documenting reflecting upon knowledge constructs-a series of ideas, approaches methods taken from existing research practice-deployed developed to support modelling the COVID-19 pandemic. Structured independent commentary these efforts is synthesized through iterative reflection develop: evidence effectiveness value in this context; open problems which communities may focus; guidance for future activity type recommendations safeguard achievements promote, advance, secure prepare collaborations kind. In describing comparing a related projects that were undertaken unprecedented conditions, our hope unique report, its rich interactive supplementary materials, will guide scientific community embracing observation, analysis data as well disseminating findings. Equally we encourage engage with impactful science addressing emerging challenges. If are successful, showcase stimulate mutually beneficial engagement complementary expertise address significance epidemiology beyond. See https://ramp-vis.github.io/RAMPVIS-PhilTransA-Supplement/. This article part theme issue 'Technical challenges real-life epidemics examples overcoming these'.
Language: Английский
Citations
15
Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, Journal Year: 2022, Volume and Issue: 380(2233)
Published: Aug. 15, 2022
Well parameterized epidemiological models including accurate representation of contacts are fundamental to controlling epidemics. However, age-stratified typically estimated from pre-pandemic/peace-time surveys, even though interventions and public response likely alter contacts. Here, we fit models, re-estimation relative contact rates between age classes, data describing the 2020–2021 COVID-19 outbreak in England. This includes population size, cases, deaths, hospital admissions results Coronavirus Infection Survey (almost 9000 observations all). Fitting stochastic compartmental such detailed is extremely challenging, especially considering large number model parameters being (over 150). An efficient new inference algorithm ABC-MBP combining existing approximate Bayesian computation (ABC) methodology with model-based proposals (MBPs) applied. Modified inferred alongside time-varying reproduction numbers that quantify changes overall transmission due pandemic response, proportions asymptomatic hospitalization deaths. These inferences robust a range assumptions values cannot be available data. shown enable reliable joint analysis complex yielding consistent parametrization dynamic can inform data-driven health policy interventions. article part theme issue 'Technical challenges modelling real-life epidemics examples overcoming these'.
Language: Английский
Citations
13
Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, Journal Year: 2022, Volume and Issue: 380(2233)
Published: Aug. 15, 2022
Pandemic management requires that scientists rapidly formulate and analyze epidemiological models in order to forecast the spread of disease effects mitigation strategies. Scientists must modify existing create novel ones light new biological data policy changes such as social distancing vaccination. Traditional scientific modeling workflows detach structure a model -- its submodels their interactions from implementation software. Consequently, incorporating local components may require global edits code-base through manual, time-intensive, error-prone process. We propose compositional framework uses high-level algebraic structures capture domain-specific knowledge bridge gap between how think about code implements them. These structures, grounded applied category theory, simplify expedite tasks specification, stratification, analysis, calibration. With made explicit, also become easier communicate, criticize, refine stakeholder feedback.
Language: Английский
Citations
10
Agronomy, Journal Year: 2023, Volume and Issue: 13(11), P. 2844 - 2844
Published: Nov. 19, 2023
The application of data science (DS) techniques has become increasingly essential in various fields, including epidemiology and climatology agricultural production systems. In this sector, traditionally large amounts are acquired, but not well-managed -analyzed as a basis for evidence-based decision-making processes. Here, we present comprehensive step-by-step guide that explores the use DS managing epidemiological climatological within rice systems under tropical conditions. Our work focuses on using multi-temporal dataset associated with monitoring diseases climate variables Colombia during eight years (2012–2019). study comprises four main phases: (I) cleaning organization to ensure integrity consistency dataset; (II) management involving web-scraping acquire information from free databases, like WordClim Chelsa, validation against situ weather stations, bias removal enrich (III) visualization effectively represent gathered information, (IV) basic analysis related clustering climatic characterization rice-producing areas Colombia. our work, process evaluation conducted based errors (r, R2, MAE, RSME) metrics. addition, phase II, was PCA K-means algorithm. Understanding association is pivotal predicting mitigating disease outbreaks areas. research underscores significance By applying protocol responsible tools, provides solid foundation further into dynamics interactions regions other crops, ultimately contributing more informed processes agriculture.
Language: Английский
Citations
4
Preventive Veterinary Medicine, Journal Year: 2024, Volume and Issue: 228, P. 106233 - 106233
Published: May 25, 2024
Epidemiological modeling is a key lever for infectious disease control and prevention on farms. It makes it possible to understand the spread of pathogens, but also compare intervention scenarios even in counterfactual situations. However, actual capability decision makers use mechanistic models support timely interventions limited. This study demonstrates how artificial intelligence (AI) techniques can make epidemiological more accessible farmers veterinarians, transform such into user-friendly decision-support tools (DST). By leveraging knowledge representation methods, as textual formalization model components through domain-specific language (DSL), co-design DST becomes efficient collaborative. facilitates integration explicit expert practical insights process. Furthermore, utilization AI software engineering enables automation web application generation based existing models. simplifies development DST, tool designers focus identifying users' needs specifying expected features meaningful presentations outcomes, instead wasting time writing code wrap apps. To illustrate this approach, we consider example Bovine Respiratory Disease (BRD), tough challenge fattening farms where young beef bulls often develop BRD shortly after being allocated pens. multi-factorial, multi-pathogen that difficult anticipate control, resulting massive antimicrobials mitigate its impact animal health, welfare, economic losses. The developed from an empowers users, including customize their specific farm conditions. them effects various outcomes associated with different farming practices, decide balance reduction antimicrobial usage (AMU). generic method presented article illustrates potential methods enhance co-creation veterinary epidemiology. corresponding pipeline distributed open-source software. these advancements, research aims bridge gap between theoretical field.
Language: Английский
Citations
1
Published: April 19, 2023
Throughout the COVID-19 pandemic, visualizations became commonplace in public communications to help people make sense of world and reasons behind government-imposed restrictions. Though adult population were main target these messages, children affected by restrictions through not being able see friends virtual schooling. However, daily models visualizations, pandemic response provided a way for understand what data scientists really do new routes engagement with STEM subjects. In this paper, we describe development an interactive accessible visualization tool be used workshops explain computational modeling diseases, particular COVID-19. We detail our design decisions based on approaches evidenced effective engaging such as unplugged activities interactivity. share reflections learnings from delivering 140 assess their effectiveness.
Language: Английский
Citations
3
Interacting with Computers, Journal Year: 2023, Volume and Issue: 35(5), P. 744 - 761
Published: Aug. 28, 2023
Abstract This paper draws on diverse psychological, behavioural and numerical literature to understand some of the challenges we all face in making sense large-scale phenomena use this create a road map for HCI responses. body knowledge offers tools principles that can help researchers deliver value now, but also highlights future research. The is framed by looking at patterns information highlight common misunderstandings arise—not just politicians general public many academic community. does not have answers this, hope it provides and, perhaps more importantly, raises questions need address as scientific technical communities.
Language: Английский
Citations
2
Published: Sept. 28, 2023
In this paper, we present an approach which couples a calibration algorithm for compartmental model of infection dynamics with graphical user interface allows to visualise the modeling results and simulate control measures aimed at curtailing spread infection. Unlike most popular approaches related visualisation disease dynamics, our method simultaneously obtain parameter values based on epidemic data change these in interactive mode. The simulation tool built according principle is intended help interdisciplinary teams objective subjective (domain-specific) criteria. We demonstrate usage resulting framework using influenza outbreak Saint Petersburg two seasons.
Language: Английский
Citations
1